Computer analysis of digital images of biological material is known as image cytometry. In image cytometry, computer controlled cameras take magnified images of cellular material then analyze the digital images to locate objects and subsequently identify (classify) some of these objects as cells. The cells are then examined for various purposes, such as determining whether the cells are healthy or cancerous. Typically, biological material is first stained to increase visualization of cellular structure or chemical composition. Certain stains or proteins bind specifically, and proportionally, to certain parts of cells or their constituents, for example, surface proteins or DNA. One example of this is Feulgen staining, which proportionally binds a stain to the DNA, which means that the more DNA there is, the darker the staining. Once DNA is stained proportionally, which in some instances can be referred to as stoichiometrically, the total amount and relative distribution of the DNA in the nucleus of a cell can be measured.
Image cytometry can be used to scan and analyze DNA stained cells to determine whether, for example, the cells have malignancy associated changes (MAC); MAC are changes associated with the spatial distribution of DNA in non-cancerous cells, MAC changes appears more frequently when a cancer is present in other cells. MAC is discussed, for example, in Finch, et al., Malignancy Associated Changes in Buccal Smears, Acta Cytologica 15: 46-49 (1971); Klawe et al., Malignancy Associated Changes (MAC) in Cells of Buccal Smears detected by means of Objective Image Analysis, Acta Cytologica 18: 30-33 (1974); U.S. Pat. No. 5,889,881; U.S. Pat. No. 6,026,174. However, it has been difficult to reliably assess the presence of MAC. For example, DNA staining using the Feulgen method may still be proportional, yet vary in overall darkness, from batch to batch due to minor variations in temperature, chemical concentrations, hydrolysis times, chromatin compactness, or other factors.
Accordingly, there has gone unmet a need for improved computer-implemented programs suitable for image cytometry that can correct or reduce variations due to staining. There has also gone unmet a need for reliable methods of detecting MAC in cells. The present invention provides these and other advantages.